Truyen Tran

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Svetha VenkateshProfessor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Dinh PhungProfessor, Monash UniversityVerified email at monash.edu
Hoa Khanh DamProfessor in Software Engineering, University of WollongongVerified email at uow.edu.au
Sunil GuptaProfessor, Head of AI Optimization and Materials Discovery, Deakin UniversityVerified email at deakin.edu.au
Wei LuoDeakin UniversityVerified email at deakin.edu.au
Trang PhamSoftware Engineer, GoogleVerified email at google.com
Aditya GhoseProfessor of Computer Science, University of WollongongVerified email at uow.edu.au
Santu RanaAssociate Professor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Vuong LeDeakin UniversityVerified email at deakin.edu.au
Phuoc NguyenResearch Lecturer, A2I2, Deakin UniversityVerified email at deakin.edu.au
Kien DoApplied Artificial Intelligence Institute (A2I2), Deakin UniversityVerified email at deakin.edu.au
Hung LeDeakin UniversityVerified email at deakin.edu.au
John GrundyAustralian Laureate Fellow and Professor of Software Engineering, Faculty of IT, Monash UniversityVerified email at monash.edu
Michael BerkDeakin UniversityVerified email at deakin.edu.au
Thao Minh LeDeakin UniversityVerified email at deakin.edu.au
Thin NguyenSenior Research Lecturer, Deakin University, AustraliaVerified email at deakin.edu.au
Morakot Choetkiertikul, Ph.D.Lecture at Faculty of ICT, Mahidol UniversityVerified email at mahidol.ac.th
Tu Dinh NguyenCanvaVerified email at canva.com
Chandan KarmakarSenior Lecturer, School of Information Technology, Deakin UniversityVerified email at deakin.edu.au
Hung BuiResearch Scientist, Google DeepMindVerified email at google.com

Truyen Tran

Associate Professor | Head of AI, Health and Science @ Deakin University

Verified email at deakin.edu.au - Homepage

deep learning machine reasoning artificial social intelligence AI for science AI for health


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Guidelines for developing and reporting machine learning predictive models in biomedical research: A multidisciplinary view W Luo, D Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, ... Journal of medical Internet research 18 (12), 2016	612	2016
Predicting healthcare trajectories from medical records: A deep learning approach T Pham, T Tran, D Phung, S Venkatesh Journal of Biomedical Informatics 69, 218--229, 2017	453	2017
Deepr: a convolutional net for medical records P Nguyen, T Tran, N Wickramasinghe, S Venkatesh IEEE journal of biomedical and health informatics 21 (1), 22-30, 2017	377*	2017
DeepCare: A deep dynamic memory model for predictive medicine T Pham, T Tran, D Phung, S Venkatesh PAKDD, 30-41, 2016	343	2016
Learning regularity in skeleton trajectories for anomaly detection in videos R Morais, V Le, T Tran, B Saha, M Mansour, S Venkatesh In 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR …, 2019	249	2019
Automatic feature learning for predicting vulnerable software components HK Dam, T Tran, T Pham, SW Ng, J Grundy, A Ghose IEEE Transactions on Software Engineering, 2018	220*	2018
Hierarchical conditional relation networks for video question answering TM Le, V Le, S Venkatesh, T Tran CVPR'20, 2020	213	2020
Lessons learned from using a deep tree-based model for software defect prediction in practice HK Dam, T Pham, SW Ng, T Tran, J Grundy, A Ghose, T Kim, CJ Kim MSR'19, 2019	206*	2019
Catastrophic forgetting and mode collapse in GANs H Thanh-Tung, T Tran 2020 International Joint Conference on Neural Networks (IJCNN), 1-10, 2020	182	2020
Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM) T Tran, TD Nguyen, D Phung, S Venkatesh Journal of Biomedical Informatics, 2015	179	2015
Column networks for collective classification T Pham, T Tran, D Phung, S Venkatesh AAAI'17, 2017	176	2017
A deep learning model for estimating story points M Choetkiertikul, HK Dam, T Tran, T Pham, A Ghose, T Menzies IEEE Transactions on Software Engineering, DOI:10.1109/TSE.2018.2792473, 2018	171	2018
Explainable software analytics HK Dam, T Tran, A Ghose ICSE'18, 2018	160	2018
Graph transformation policy network for chemical reaction prediction K Do, T Tran, S Venkatesh Proceedings of the 25th ACM SIGKDD International Conference 609, 750-760, 2019	151	2019
Improving generalization and stability of Generative Adversarial Networks H Thanh-Tung, T Tran, S Venkatesh ICLR'19, 2019	137	2019
Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments T Tran, W Luo, D Phung, R Harvey, M Berk, RL Kennedy, S Venkatesh BMC Psychiatry (ECR Best paper awarded by CRESP), 2014	134	2014
A deep language model for software code HK Dam, T Tran, T Pham FSE'16 Workshop on Naturalness of Software (NL+SE), 2016	124	2016
Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry S Gupta, T Tran, W Luo, D Phung, RL Kennedy, A Broad, D Campbell, ... BMJ Open, 2014	102	2014
Nonnegative shared subspace learning and its application to social media retrieval SK Gupta, D Phung, B Adams, T Tran, S Venkatesh KDD'10, 1169-1178, 2010	92	2010
Ordinal Boltzmann machines for collaborative filtering TT Truyen, DQ Phung, S Venkatesh UAI'09 (Best paper runner up), 548-556, 2009	84	2009

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